Scheduling patients in an ambulatory surgical center

This paper presents a deterministic approach to schedule patients in an ambulatory surgical center (ASC) such that the number of postanesthesia care unit nurses at the center is minimized. We formulate the patient scheduling problem as new variants of the no‐wait, two‐stage process shop scheduling problem and present computational complexity results for the new scheduling models. Also, we develop a tabu search‐based heuristic algorithm to solve the patient scheduling problem. Our algorithm is shown to be very effective in finding near optimal schedules on a set of real data from a university hospital's ASC. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

A continuous-review inventory model with constant resupply time and defective items

As a result of imperfect production and inspection by suppliers, pilferage, and/or damage in transit, it is common that procurement orders may contain defective items. This article deals with a continuous-review inventory system with Poisson demand arrivals and constant resupply time. Items in resupply lots may not be of perfect quality. The operating characteristics of such a system are analyzed. For purposes of computational savings, an approximation scheme for the operating characteristics is presented. As a result of the approximation, the determination of the optimal ordering policy becomes much simpler. Extensive numerical tests suggest that the approximation scheme is very effective in giving the optimal or near-optimal ordering policies for such a system.     

Validation of a strategy for harbor defense based on the use of a min‐max algorithm receding horizon control law

We present a validation of a centralized feedback control law for robotic or partially robotic water craft whose task is to defend a harbor from an intruding fleet of water craft. Our work was motivated by the need to provide harbor defenses against hostile, possibly suicidal intruders, preferably using unmanned craft to limit potential casualties. Our feedback control law is a sample‐data receding horizon control law, which requires the solution of a complex max‐min problem at the start of each sample time. In developing this control law, we had to deal with three challenges. The first was to develop a max‐min problem that captures realistically the nature of the defense‐intrusion game. The second was to ensure the solution of this max‐min problem can be accomplished in a small fraction of the sample time that would be needed to control a possibly fast moving craft. The third, to which this article is dedicated, was to validate the effectiveness of our control law first through computer simulations pitting a computer against a computer or a computer against a human, then through the use of model hovercraft in a laboratory, and finally on the Chesapeake Bay, using Yard Patrol boats. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 247–259, 2016     

Military spending and growth: a small open economy stochastic growth model

The paper analyzes the effects of military spending on economic growth in a small open stochastic endogenous growth model involving the supply-side and demand-side effects produced by military spending. We show that a rise in the military spending affects economic growth through four channels, including the crowding-out effect, the spin-off effect, the resource mobilization effect, and the portfolio effect. The net effect which depends on these four channels is ambiguous. Hence, we demonstrate that there exists an optimal defense burden that maximizes the economic growth rate.     

Economic design of a two-stage control chart based on both performance and surrogate variables

The traditional approach to economic design of control charts is based on the assumption that a process is monitored using only a performance variable. If, however, the performance variable is costly to measure and a less expensive surrogate variable is available, the process may be more efficiently controlled by using both performance and surrogate variables. In this article we propose a model for economic design of a two-stage control chart which uses a highly correlated surrogate variable together with a performance variable. The process is assumed to be monitored by the surrogate variable until it signals out-of-control behavior, then by the performance variable until it signals out-of-control behavior or maintains in-control signals for a prespecified amount of time, and the two variables are used in alternating fashion. An algorithm based on the direct search method of Hooke and Jeeves [6] is used to find the optimum values of design parameters. The proposed model is applied to the end-closure welding process for nuclear fuel to compute the amount of reduction in cost compared with the current control procedure. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 958–977, 1999     

Decomposition algorithms for the maximum-weight connected graph problem

Given a positive integer R and a weight for each vertex in a graph, the maximum-weight connected graph problem (MCG) is to find a connected subgraph with R vertices that maximizes the sum of their weights. MCG has applications to communication network design and facility expansion. The constrained MCG (CMCG) is MCG with a constraint that one predetermined vertex must be included in the solution. In this paper, we introduce a class of decomposition algorithms for MCG. These algorithms decompose MCG into a number of small CMCGs by adding vertices one at a time and building a partial graph. They differ in the ordering of adding vertices. Proving that finding an ordering that gives the minimum number of CMCGs is NP-complete, we present three heuristic algorithms. Experimental results show that these heuristics are very effective in reducing computation and that different orderings can significantly affect the number of CMCGs to be solved. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 817–837, 1998     

Operating characteristics of a two-echelon inventory system for repairable and consumable items under batch ordering and shipment policy

In this article we have generalized previous models on multiechelon recoverable inventory systems to cover the cases of batch ordering and shipment policy, and when items can either be repaired or condemned. The batch ordering and shipment policy is appropriate when the setup cost for shipment and order and/or the demand rates of the items are relatively high. The operating characteristics of such a system have been studied. Specifically, the probability distribution of backorder levels at the bases are analyzed for different repair-time distributions. An approximation scheme is proposed for this distribution, and is evaluated using extensive simulation results. The results indicate that the scheme is very effective in providing near-optimal stocking levels in such a system.     

Global planning of accelerated degradation tests based on exponential dispersion degradation models

The accelerated degradation test (ADT) is an efficient tool for assessing the lifetime information of highly reliable products. However, conducting an ADT is very expensive. Therefore, how to conduct a cost-constrained ADT plan is a great challenging issue for reliability analysts. By taking the experimental cost into consideration, this paper proposes a semi-analytical procedure to determine the total sample size, testing stress levels, the measurement frequencies, and the number of measurements (within a degradation path) globally under a class of exponential dispersion degradation models. The proposed method is also extended to determine the global planning of a three-level compromise plan. The advantage of the proposed method not only provides better design insights for conducting an ADT plan, but also provides an efficient algorithm to obtain a cost-constrained ADT plan, compared with conventional optimal plans by grid search algorithms.     

Callable products with dependent demands

Capacity providers such as airlines often sell the same capacity to different market segments at different prices to improve their expected revenues. The absence of a secondary market, due to the nontransferability of airline tickets, gives rise to an opportunity for airlines to broker capacity between consumers with different willingness to pay. One way to broker capacity is by the introduction of callable products. The idea is similar to callable bonds where the issuer has the right, but not the obligation, to buy back the bonds at a certain price by a certain date. The idea of callable products was introduced before under the assumption that the fare-class demands are all independent. The independent assumption becomes untenable when there is significant demand recovery (respectively, demand cannibalization) when lower fares are closed (respectively, opened). In this case, consumer choice behavior should be modeled explicitly to make meaningful decisions. In this paper, we consider a general consumer choice model and develop the optimal strategy for callable products. Our numerical study illustrates how callable products are win-win-win, for the capacity provider and for both high and low fare consumers. Our studies also identify conditions for callable products to result in significant improvements in expected revenues.     

An analytic basis for decision support in negotiations

Mediators increase the effectiveness of negotiation processes. The art of mediation includes interpersonal skills, ability to convince, and proficiency in argumentation. The science of mediation represents an analytical approach to problem solving, a systematic analysis of the process, of players' positions, and of their goals, aspirations, and concessions. Analytical tools for mediation can be used by mediators, but these tools can also support negotiators in their analysis, verification of their positions, and choices. The knowledge of effective and safe alternatives, of sets of compromises, and the knowledge of the possible outcomes of concessions may be used to develop an effective strategy and to increase a negotiator's bargaining power. Models to analyze alternatives, to verify concessions made by the opponents, to determine effective alternatives, and to search for solutions that yield mutual gains, to aggregate opponents' proposals, to look for coalition members, and to simulate some of the actions of a mediator are discussed in the article.